Tag Archive: analysis

In our Revolvers' Dollars series, we built a dataset covering all active firm lobbyists from 1998—2012. Here, we describe the methodology behind our dataset, and offer some cautions on these data and methods.

With the U.S. Senate expected to take up gun legislation next week and recent passing of gun laws in Connecticut, Colorado and Maryland, we put together a tool kit on the issues around gun rights and gun control. For more information, you can follow the money, influence and news on the issue of gun control and gun rights in the U.S. at our resource page.
Keep reading for information about state legislation, swing votes in the Senate, political spending by gun rights and gun control groups, details on how they lobby Congress and where they are airing TV issue ads.

One of the emerging post-campaign narratives is that all the outside money (more than $1.3 billion) that poured into the 2012 election didn’t buy much in the way of victories. And as we dig through the results in detail (our extensive data visualizations and analysis are below), the story holds up: we can find no statistically observable relationship between the outside spending and the likelihood of victory.
Looking closely at the data helps to clarify and explore this emerging narrative in numerous ways. It also helps us to see some other smaller effects of money. It appears that candidate spending may have mattered a bit more than outside spending, especially for Democrats. It also appears that outside spending may have contributed slightly to the vote share, though not to the probability of victory.
This post is based on House results, both because looking at the House gives us a larger sample size, and because there’s more of a likelihood that money could make a difference in House races, given the smaller size of House seats (compared to the Senate), the recent redistricting and the fact that we’ve had three House elections in a row with high turnover. (We’ll come back to the Senate soon, we promise)
First an overview. As of September 6, two months before the election, the Cook Political Report listed 90 House seats as either likely for one party, lean for one party, or toss-ups. These were the seats where money could make a difference if it were to make one. (Before we proceed, a few caveats: 1. The candidate spending totals are through October 17; and 2. For purposes of the analysis we include outcomes still pending final approval.)
Outside spending on these 90 seats was just over a quarter of a billion: $250,656,656, and candidate spending was just short of $300 million: $297,947,7717. In the 25 toss-up races, candidates spent $100,164,189; outside groups spent $140,043,821.

Over the weekend I was clearing out my RSS, and was pleasantly surprised to find Sunlight's work in an unexpected place. TheWashCycle is my favorite DC bike blog, and its author has started a series of posts designed to address arguments that are commonly faced by cycling advocates. One of those is that cyclists don't pay for roads — that the gas tax pays for them — and consequently folks on bikes aren't entitled to the use of roads, or are less entitled to space on the road than motorists, or shouldn't have a say in how roads are built.

As it turns out, the assumption that cyclists don't pay for roads is wrong. The WashCycle post linked to some work that we did for Pew's Subsidyscope project, which shows that gas taxes are paying for a decreasing share of our roads. In 2007 taxes and fees related to auto use covered only half the bill. The shortfall is made up by general revenues and debt — and though the specifics of the story play out differently from state to state it's safe to say that cyclists pay taxes that help build roads.

I mention all this not simply to highlight some pro-cyclist propaganda — though of course, as a daily bike commuter, I'm glad to do that, too — but rather to point this out as an example of what open government data can accomplish.

Government is releasing data at a breakneck pace, and it is just getting started. One interesting side effect of our National Data Catalog is that we're regularly parsing all of the data on data.gov, and we're able to do interesting things with the aggregate metadata. By parsing out the release date for each dataset on data.gov, and grouping each release by quarter though it's easy to see that since the second quarter of 2009-- when Data.gov was released, the federal government has released more raw datasets than it ever has in the past. Take a look at what's happened after Data.gov launched: